WEBINAR: Data Streaming Success Stories with Kafka - How Qlik and Confluent Keep Your Data Fresh - 10 June 2021

 

Data Science Central Webinar Series Event Data Streaming Success Stories with Kafka - How Qlik and Confluent Keep Your Data Fresh Join us for this latest DSC Webinar on June 10th, 2021 Converting production databases into live data streams for Apache Kafka can be labour-intensive and costly. As Kafka architectures grow, complexity also rises as data teams begin to configure clusters for redundancy, partitions for performance, as well as for consumer groups for correlated analytics processing. In this latest Data Science Central webinar, you’ll discover how Qlik’s data integration platform lets organizations automatically produce real-time transaction streams into Kafka, Confluent Platform, or Confluent Cloud, deliver faster business insights from data, enable streaming analytics, as well as streaming ingestion for modern analytics. Speakers:   Adam Mayer, Senior Technical Product Marketing Manager - Qlik     Rankesh Kumar, Partner Solutions Engineer - Confluent    Hosted by:   Sean Welch, Host and Producer - Data Science Central   Title:  Data Streaming Success Stories with Kafka - How Qlik and Confluent Keep Your Data Fresh Date:  Thursday, June 10th, 2021 Time:  9:00 AM - 10:00 AM PST   Space is limited so please register early: Reserve your seat now

6 side hustles for an aspiring data scientist by Ahmad Bin Shafiq via @kdnuggets

The ideas the author is about to suggest would certainly help you upskill, earn a good side income as a data scientist, and most importantly, be your own boss.

This was interesting.

Kedro: The Best Python Framework for Data Science!! by Josue Luzardo Gebrim via @Medium

Kedro: Python Framework for data sciences!

I liked this and all the code snippets. It certainly introduced me to something I was not familiar with and it gives me something to investigate further.

String Interning in Python: A Hidden Gem That Makes Your Code Faster by Yang Zhou via @Medium

Level up the speed of string comparisons.

This helped my code and is well worth a read.

16 Must-Know Bash Commands for Data Scientists by Giorgos Myrianthous via @TDataScience

Exploring some of the most commonly used bash commands.

This was really useful as I really struggle with anything in the Unix or Linux worlds. I love that you see clear examples for each of the commands.

400x times faster Pandas Data Frame Iteration by Satyam Kumar via @TDataScience

Avoid using iterrows() function.

I liked his conclusion and he makes some good points - just adding a dictionary is probably a quick and easy change to code which can make a big difference whilst avoiding the reworking of code.

WEBINAR: Putting the Science Back in Data Science - 26 May 2021

 

Sponsored News from Data Science Central

Putting the Science Back in Data Science May 26, 2021 | 11.00 am ET - 60 min including Q&A Register now Hi there, Do you remember the old days when you had hand-code Gradient Descent or manually tune your hyperparameters? Over the last 20 years, the machine learning tool stack has improved considerably and now includes tools like Keras and Scikit. DataRobot has kept pace with this acceleration and offers a wide set of tools for data scientists. In this webinar, we show how to extend Python to try multiple modeling approaches (anomaly, time series, multiclass), create sophisticated feature engineering across multiple datasets, and even build hundreds of diverse models with a few lines of code. We’ll discuss how data scientists save time, get more accurate results, and most important, create value for their organizations. During this webinar, you will learn: How you can use Python with DataRobot to build powerful model factories How you can use Feature Discovery to accelerate feature engineering and improve your models How to eliminate AI-related risks by adopting MLOps and automatic model retraining Register now

Your Python Output Can Be Prettier by Christopher Tao via @TDataScience

 From basic to advance usage of the Python Pretty Printer library.

I found this really interesting and anything that improves the output from a program has got to be good as quite often output can be dreadful.

Practical SQL for Data Analysis by/via @be_haki

In this epic post, Haki Benita shows how to use SQL to perform fast and efficient data analysis. Pivot tables, subtotals, linear regression, binning, and interpolation can all be done with SQL and in many cases, that's the best approach. There's a lot of detail here and a linked index makes it easy to jump around.

I love SQL and I am so much more comfortable writing code in it. I can however see times when Python and Pandas would work better.

Don’t Start Coding With Python — Begin With C by Mohammed Ayar via @BttrProgramming

Don’t fall for the hype surrounding Python. You might regret it later.

An interesting read that put a different spin on things.

WEBINAR: How to Take Your Data Visualizations to the Next Level - 18 May 2021

 

Data Science Central Webinar Series Event

How to Take Your Data Visualizations to the Next Level Join us for this latest DSC Webinar on May 18th, 2021 When you choose the right visualization to highlight the most important aspect of your data, you can illuminate new insights and communicate them more persuasively, resulting in smarter actions and bigger outcomes for your business. In this latest Data Science Central webinar, the Product Manager for Visualizations at Qlik®, Patric Nordström, and best-selling author and strategic advisor, Bernard Marr, will discuss important trends, new insights and best practices in data visualization today. Discover how to inspire effective action in your organization – by telling your data story in the clearest, most compelling way possible. Speakers:   Patric Nordström, Director, Product Management - Qlik     Bernard Marr, Best-selling author, Futurist, Strategic Advisor   Hosted by:   Sean Welch, Host and Producer - Data Science Central   Title:  How to Take Your Data Visualizations to the Next Level Date:  Tuesday, May 18th, 2021 Time:  9:00 AM - 10:00 AM PST   Space is limited so please register early: Reserve your seat now

Shogun: An Underrated Python Machine-learning Package by @emmettboudgie via @TDataScience

Taking a look at the Shogun package for Python, and why it is a less-used library for machine learning in Python.

I had never heard of this package but it looks like a good one to add to my arsenal of machine learning packages for Python.

3 Python Pandas Tricks for Efficient Data Analysis by @snr14 via TDataScience

Explained with examples. Pandas is one of the predominant data analysis tools.

Some handy hints in Python that may fix some minor issues in your code that you hadn't realised could be fixed so easily.

How to Run 40 Regression Models with a Few Lines of Code by Ismael Araujo via TDataScience

Learn how to run over 40 machine learning models using Lazy Predict for regression projects.

This is a real timesaver and very useful if you hadn't come across it before.

WEBINAR: Natural Language Trends in Visual Analysis - 13 May 2021

 

Data Science Central Webinar Series Event

Natural Language Trends in Visual Analysis Join us for this latest DSC Webinar on May 13th, 2021 Natural language processing has garnered interest in helping people interact with computer systems to make sense and meaning of the world. In the area of visual analytics, natural language has been shown to help improve the overall cognition of visualization tasks. In this Data Science Central webinar, Vidya Setlur, Principal Research Scientist at Tableau, will discuss how natural language can be leveraged in various aspects of the analytical workflow ranging from smarter data transformations and visual encodings to autocompletion and supporting analytical intent. Vidya will also examine the implications of these innovations as well as future directions for research in this space. Speakers:   Vidya Setlur, Principal Research Scientist - Tableau   Hosted by:   Sean Welch, Host and Producer- Data Science Central   Title:  Natural Language Trends in Visual Analysis Date:  Tuesday, May 13th, 2021 Time:  9:00 AM - 10:00 AM PST   Space is limited so please register early: Reserve your seat now

WEBINAR: How to deliver quality data for analytics - 12 May 2021

 

Please register to join Soda Live on May 12, an event for organizations reliant on good data quality and integrity to transform how they operate.

 

Soda Live is bringing together members of the data community to discuss how to deliver quality data for analytics and data products that everyone can trust. Panelists include:

 

• Dr. Kinda El Maarry, Global Head of Data Governance at HelloFresh
• Sarah Catanzaro, Partner at Amplify Partners
• Dr. Alexander Borek, Head of Data at Zalando
• Joseph Jacks, Partner at COSS
• Martijn Spaan, Head of Data & Insights at NN Investment Partners

 

The Soda Team will present the Soda platform and developer tools showcasing core capabilities for automated monitoring, testing and validation, data fitness and collaboration. We'll be sharing practitioner tips and inspiring you with best practices that you can put to use straight away!

 

There are two broadcasts taking place at 4.00pm CEST and 4.00pm EDT.

 

If your business relies on quality data, this is a must-attend event for you.

 

Register Now

Top 10 Data Science Courses to Take in 2021 by @coursera via @kdnuggets

Whether you are getting started with Data Science / Machine Learning or are an experienced professional looking to learn something new, check out these top 10 data science courses for 2021.

It looks like I need to do some new online courses.